Neural network training by integration of adjoint systems of equations forward in time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies

Fast temporal neural learning using teacher forcing

A neural network is trained to output a time dependent target vector defined over a predetermined time interval in response to a time dependent input vector defined over the same time interval by applying corresponding elements of the error vector, or difference between the target vector and the actual neuron output vector, to the inputs of corresponding output neurons of the network as corrective feedback. This feedback decreases the error and quickens the learning process, so that a much smaller number of training cycles are required to complete the learning process. A conventional gradient descent algorithm is employed to update the neural network parameters at the end of the predetermined time interval. The foregoing process is repeated in repetitive cycles until the actual output vector corresponds to the target vector. In the preferred embodiment, as the overall error of the neural network output decreasing during successive training cycles, the portion of the error fed back to the output neurons is decreased accordingly, allowing the network to learn with greater freedom from teacher forcing as the network parameters converge to their optimum values. The invention may also be used to train a neural network with stationary training and target vectors

Wandering Spleen in an Adult Man Associated With the Horseshoe Kidney

Introduction: A wandering spleen occurs when there is a laxity of the ligaments that fix the spleen in its normal anatomical position. Case Presentation: This is a case report of a wandering spleen with horseshoe kidney in a 29-year-old male admitted with acute lower abdominal pain and vomiting to emergency department of Shariati hospital in Isfahan province. Sonographic examination showed a homogeneous 21 × 15 × 8 cm mass in the lower part of the abdomen and pelvis associated with a horseshoe kidney. Laparotomy confirmed the clinical and ultrasound findings. Conclusions: The association of horseshoe kidney with a wandering spleen in this case may be due to an embryological anomaly

Strength of drilling fluid filter cakes

Wellbore strengthening techniques are commonly used to prevent drilling fluid losses. Current methods generally require that particles are added to the drilling fluid to hinder fracture propagation, which creates practical difficulties as the particles are often relatively large. An alternative approach is the idea of using the filter cake that forms against the wellbore rock to create a robust seal, the efficacy of which will depend on cake strength. However, little is currently understood about filter cake strength and how it is impacted by typical particulates in the drilling fluid. In this work, the strength of drilling fluid filter cakes is assessed. Furthermore, filter cake properties such as porosity and thickness that are altered by constituent particles and that affect cake strength are explored. The cake strength was measured using the hole punch test and particle properties such as particle concentration, size distribution and shape were evaluated. Representative water-based and oil-based drilling fluids were analysed to establish benchmark results, which were based on the rheological and filtration behaviours as well as filter cake properties. These results produced similar trends to those of model water-based drilling fluids composed of typical drilling fluid components, such as an increase in cake strength and a decrease in cake porosity as the barite volume fraction in the fluid increased. For these model fluids, the cake strength also increased as the particle size and cake porosity decreased whilst calcium carbonate cakes were stronger than the barite equivalents. Cake strength may have been influenced by interparticle contact surface area, which was affected by cake porosity and thickness. The relationships between particle size, pore distributions and thickness were better understood by visualising the internal structure of filter cakes, using images captured via X-ray computed tomography. The images showed that the size of the pores decreased as the particle size decreased, the cakes had a more porous bottom layer than top and the porosity decreased with filtration time. Discrete element method simulations were compared with experimental results, and relationships between cake strength and the interparticle contact surface area, determined using cake porosity and particle size, were found

DEMENTIA CAREGIVING OUTCOMES: THE IMPACT OF CAREGIVING ONSET, ROLE OCCUPANCY, AND CARE-RECIPIENT DECLINE

Dementia is characterized as a progressive loss of brain function that results in the deterioration of many cognitive and physical abilities. Alzheimer’s disease (AD) is the most common form of dementia, causing steady declines in memory, functional abilities, and mental functioning. With a projected increase of degenerative illnesses, such as AD, family caregiving for individuals with the disease is also steadily increasing. Caring for an individual with AD has been characterized as a “career,” and within this career are a number of key transitions, including the onset of caregiving. Preexisting caregiving research reveals a number of negative consequences for AD family caregivers, including depression, overload, and physical health complications. The purpose of this study was to examine how different patterns of caregiving onset (gradual and abrupt) and role occupancy (how many roles the caregiver is holding) impact mental health and physical health outcomes for AD caregivers. This study also explored how cognitive decline and behavioral problems found within the care-recipient have the potential to moderate these relationships. Cross-sectional, quantitative data from one hundred participants completing self-administered surveys was used in this study. A series of one-way ANOVAS and multiple regression analyses were conducted to address the study’s aims. Results indicated that care-recipient cognition and behavioral problems moderated the relationship between caregiving onset and mental health outcomes, including depression, role overload, and role captivity for caregivers who experienced a more abrupt entry into the caregiving role. Results suggest the importance of considering moderating factors within the caregiving career, as well as different caregiving onset transitions. Clinical implications of the findings are discussed, as well as directions for future research, including prospective caregiving research